Retail Co-location Methodology — Woodfine Projects

Retail development capital is usually committed on comparables and analyst sentiment. Whether independent demand actually converges at a site — the reason it should succeed — is assumed rather than measured.

The Woodfine co-location methodology measures it. It ranks development sites by the objective convergence of independent, capital-intensive retail operators, not by market sentiment or analyst forecasts. The framework is operationalised by the deterministic ranking system and exposed to platform users via the co-location intelligence overview.

A node qualifies when a hypermarket, a warehouse club, and a home-improvement superstore have each independently committed capital within 1.0 to 3.0 km of one another. Each operator runs its own site-selection process; convergence is independent corroboration, not a single forecast. The qualification logic, cluster formation, and the anchor adjacency requirement are the three structural inputs to the index.

For a capital allocator the index is a defensive filter: it prioritises the sites where several parties have independently validated the trade area. This article covers the Named-Anchor Model, the three operator tiers, and the five quality tiers; sibling articles describe the O-D catchment methodology, the trade-area data sources, and the catchment ranking methodology.

[edit]The Named-Anchor Model

Large-format retailers apply rigorous, data-driven site-selection criteria before committing capital to a market. When several independent operators converge on the same geographic node, that convergence signals a validated commercial corridor — a location where multiple parties have independently confirmed the trade area's strength.

The methodology sorts these operators into three tiers, by commercial function and foot-traffic contribution.

[edit]Primary Targets — the anchor

The foundational requirement for any evaluated node; the core traffic driver.

North America: Walmart Supercentre.
Europe: IKEA, as the operational baseline.

[edit]Secondary Targets — commercial support

Complementary large-format operators that validate the trade area's commercial depth. They are evaluated within a strict 1.0 km to 3.0 km catchment radius of the Primary Target.

Secondary-1 (hardware): Home Depot, Lowe's, Leroy Merlin.
Secondary-2 (warehouse club): Costco, Sam's Club, Makro.

[edit]Tertiary Targets — institutional support

Civic and institutional infrastructure that provides a non-cyclical, stable demographic baseline. Evaluated within a 5.0 km catchment radius.

Tertiary-A (healthcare): major hospitals and medical centres.
Tertiary-B (higher education): universities and colleges.

[edit]Quality tiers and site validation

Sites are evaluated on a 12-rank matrix that maps to five quality tiers, separating commodity retail nodes from the rare locations where critical commercial elements converge. The map-facing labels — Regional, District, Local, Fringe — follow the ICSC retail property hierarchy described in tier nomenclature.

Tier	Description	Commercial validation
★★★★★	Tier 5 — Full co-location	All four categories present: hardware, warehouse club, healthcare, higher education
★★★★	Tier 4 — Strong co-location	Both commercial secondaries plus one tertiary; one institutional dimension absent
★★★	Tier 3 — Partial co-location	Two categories present: a full secondary pairing, or one secondary with at least one tertiary
★★	Tier 2 — Limited co-location	One category present: hardware only, or warehouse club with a single tertiary
★	Tier 1 — Anchor only	Commercial secondaries largely absent: tertiary-only convergence, or warehouse club only

See topic-co-location-ranking-system for the complete 12-rank specification, the rank-to-tier mapping, and site counts by tier.

[edit]Strategy and application

The co-location index acts as a defensive filter for capital deployment. By focusing on Tier 4 and Tier 5 nodes, an investor prioritises sites with the highest level of independent capital validation and the strongest multi-format demographic anchors.

The methodology applies consistently across global markets by mapping regional operators to these canonical roles. A planned expansion integrates logistics and transport data to add a fourth dimension to the matrix; that expansion is forward-looking and framed per ^[ni-51-102] and ^{[osc-sn-51-721]}.

[edit]See also

[edit]Data sources

Anchor and secondary operator locations are sourced from OpenStreetMap contributors under the Open Database Licence (ODbL). Records are filtered by canonical Wikidata brand identifiers to ensure consistent chain-family matching across borders. The full chain-to-family mapping is documented in topic-retail-brand-family-taxonomy. [osm-odbl]

[edit]References

Retail park — Wikipedia, accessed 2026-06-14
Big-box store — Wikipedia, accessed 2026-06-14
DBSCAN — Wikipedia, accessed 2026-06-14